An Improved Dynamic State Estimation algorithm of Smart Grid Under Packet Losses

This paper proposes an improved dynamic state estimation (DSE) algorithm considering data packet losses between the interconnected estimators. Firstly, by integrating Holt’s two-parameter exponential smoothing and Kalman-Consensus Filtering algorithm, an improved DSE algorithm is proposed, where the prediction values are updated by considering the local estimator and neighbor estimators. Secondly, the estimation errors of all estimators are combined to obtain the estimation error dynamics of the system. Using Schur’s complement, the obtained error dynamic is converted into a bilinear matrix inequality (BMI), and the estimated optimal gain can be obtained by the iterative solution approach. Finally, the proposed algorithm was verified by the IEEE-14 test system. Simulation results confirm the effectiveness and feasibility of the proposed algorithm under data packet losses.